In the exploration for and/or the exploitation of a resource, such as hydrocarbons, from subterranean environs, there is an ongoing need to accurately characterize subterranean reservoirs of interest. Knowing the areal extent, hydrocarbon content, and fluid permeability of a hydrocarbon-bearing, subterranean reservoir is extremely important to reduce the risk of exploration and/or exploitation and conversely to increase the efficiency and/or rate of return on hydrocarbon production from the reservoir. Such information regarding the subterranean reservoir is most readily obtained from one or more wells, which are drilled through the reservoir. Drilling rates, drill cuttings, changes in drilling mud composition, and core samples from a well provide the requisite information. Logs generated by passing well logging tools through a well are also a good source of information. Logs provide valuable information concerning the rock and fluid properties of the subterranean reservoir, such as porosity, fluid identification, and shale volume. Exemplary logs include resistivity, gamma ray, density, compressional velocity, shear velocity, and neutron logs.
Since most logs only measure rock and fluid properties only a few feet from the well bore and the vast majority of the reservoir is not penetrated by wells, the logs are unfortunately only capable of characterizing an extremely small fraction of a reservoir. Furthermore, the act of drilling stresses the rock surrounding the well bore, thereby changing the rock properties and introducing error into measurements obtained by well logging and core analysis. Additional information, such as fluid pressure and reservoir effective permeability-thickness, is obtained from flow tests performed after a well is drilled. However, such tests yield information on a small percentage of the total productive reservoir. Thus, a long-standing need exists to accurately characterize rock and fluid properties across substantially the entirety of a subterranean reservoir and, in particular, to accurately characterize rock and fluid properties in regions of the reservoir which are not sampled by wells.
Well data has conventionally been extrapolated away from the well bore to characterize the entirety of the reservoir when well data is limited. Conventional extrapolation techniques depict the subterranean reservoir as a plurality of three-dimensional arrays of blocks or cells that are integrated together to form a three-dimensional model of the reservoir. Typically, the X, Y and Z coordinates of each block are determined in both absolute elevation and stratigraphic surfaces and search algorithms are used to determine relative data points in the vicinity of each block. In addition, the rock properties of each block are assigned by means of estimation methods, such as distance-based methods using interpolated averaging methods which are based upon nearby data values and geostatistical methods which account for both the distance and spatial continuity of rock properties.
Seismic surveys have also been used to provide seismic information over the portions of the subterranean reservoir that are not sampled by a well. Seismic surveys can sample substantially the entire subterranean reservoir of interest, and therefore, represent an extremely valuable measurement of inter well and/or undrilled reservoir properties. Impact devices, such as vibratory sources, gas guns, air guns, explosives and weight drops, are employed at the earthen surface or in a well bore as a seismic source to generate shear and compressional waves in the subterranean strata. These waves are transmitted through the subterranean strata, reflected at changes in acoustic impedance, and recorded, usually at the earthen surface, by recording devices placed in an array. The seismic data is usually recorded in a plurality of amplitude volumes, for example angle of incidence, time of acquisition, shooting direction, and primary or mode-converted shear reflections. This recorded data is typically processed using software that is designed to minimize noise and preserve reflection amplitude. The seismic surveys are ultimately evolved into three-dimensional data sets representing a direct measurement of the surfaces of the rock that define the subterranean reservoir. The data sets are increasingly used to evaluate and map subsurface structures for the purpose of exploring or exploiting oil, gas or mineral reserves. However, seismic data has traditionally been utilized mainly in three-dimensional geologic models for the purpose of defining the top and base of the model.
Recorded seismic data has also been processed by software to convert the data to a value of acoustic impedance. Acoustic impedance, which is a measure of the opposition of the flow of sound through a surface, is an inherent rock property. A number of seismic inversion software packages are commercially available which process the seismic data, converting the data to a distribution of seismically-derived acoustic impedance over time or depth within the geologic volume. An exemplary seismic inversion software package is available under the trade name “TDROV” from CGG Americas Inc., 16430 Park Ten Place, Houston, Tex. 77084, USA. Such inversion software uses an error minimization algorithm to determine the best fit for the acoustic impedance derived from the recorded seismic value. The values of acoustic impedance thus derived have been used to interpret subterranean zones of interest, for example by estimating the location of subterranean boundaries and the thickness of a layer, zone, formation, reservoir, etc. However, as acoustic impedance calculated by such inversion software is not constrained by the petrophysical properties of the subterranean zones of interest, the values of acoustic impedance derived from such inversion software often do not accurately reflect the actual rock and fluid properties of the subterranean zones of interest, but rather only relative values. Accordingly, interpretations of subterranean zones of interest based upon values of acoustic impedance derived by application of such inversion software are often inaccurate and therefore problematic.
One approach to obtain values of acoustic impedance from inversion software that are within an acceptable solution range, involves further constraining the results of acoustic impedance with petrophysical properties of the subterranean zone(s) of interest. In accordance with this approach, acoustic impedance is first obtained by processing recorded seismic data with inversion software as discussed above. The value of acoustic impedance derived from this software is then further inverted by means of suitable algorithms to obtain rock properties, such as porosity. As with the acoustic impedance inversion software, this rock property software includes error minimization algorithms to determine the best fit for the rock property value derived from the acoustic impedance. However, by first determining acoustic impedance from recorded seismic values, prior to sequentially determining rock properties from acoustic impedance, errors associated with the acoustic impedance determination are compounded by subsequent errors associated with the determining of rock properties from acoustic impedance. Further, seismic data for a given trace is recorded in a plurality of amplitude volumes, for example angle of incidence, time or acquisition, shooting direction, and primary reflection versus shear volume. Using the approach outlined above, each volume of seismic data recorded must be sequentially processed using seismic inversion and rock property inversion software resulting in solution ranges for rock properties for different volumes of a given seismic trace which do not overlap and therefore give rise to uncertainty of the accuracy of the results. In order to overcome the error propagation from this sequential method, all the available information and experimental data must be analyzed jointly. However, joint inversion schemes that solve only for elastic properties, such as compressional and shear velocities and densities, do not directly provide information required for important reservoir properties and would require an additional sequential step similar to that described above. Other schemes of joint inversion that solve directly for rock properties often omit constraints necessary for uncertainty reduction, such as scale constraints. For example, the thinnest layers corresponding to seismic resolution frequently do not describe properties of a scale important for reservoir performance prediction, but are limited to averages of flow-unit scale layers. Another omitted constraint is the relationship between velocity, time and thickness. Joint inversion schemes that operate in a single vertical axis scale, typically compressional wave 2-way travel time, do not optimally reconcile the location, thickness, velocity relationships of layers at flow unit scale.
For precise reservoir description, joint inversion schemes must be able to maintain consistency of properties from the thinnest flow unit to the seismic resolution to the geologic sequence, in other words, over all scales and measurement domains. The interfaces and values for the layers must be variable within physically realistic constraints to minimize the difference between the reservoir model and the seismic observations at the resolution required for reservoir response description while maintaining consistency with the geological, petrophysical constraints. Thus, the present invention recognizes a need to more effectively integrate seismic data with geologic and petrophysical models for accurate characterization of subterranean reservoirs.